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cs.SD2026
A Hybrid Discriminative and Generative System for Universal Speech Enhancement
Yinghao Liu, Chengwei Liu, Xiaotao Liang +3
Universal speech enhancement aims at handling inputs with various speech distortions and recording conditions. In this work, we propose a novel hybrid architecture that synergizes…
cs.SD2025
UniTok-Audio: A Unified Audio Generation Framework via Generative Modeling on Discrete Codec Tokens
Chengwei Liu, Haoyin Yan, Shaofei Xue +5
Generative modeling has recently achieved remarkable success across text, image, and audio domains, demonstrating powerful capabilities for unified representation learning. However…
cs.SD2025
UniSE: A Unified Framework for Decoder-Only Autoregressive LM-Based Speech Enhancement
Haoyin Yan, Chengwei Liu, Shaofei Xue +4
Neural audio codecs have largely promoted the application of language models (LMs) for speech applications. However, the effectiveness of autoregressive LM-based models in unifying…